Division of Earth Environmental System Science (Major in Environmental Engineering), Pukyong National University, Busan 48513, Republic of Korea.
Department of Environmental Engineering, Pukyong National University, Busan 48513, Republic of Korea.
Sci Total Environ. 2022 Mar 15;812:151464. doi: 10.1016/j.scitotenv.2021.151464. Epub 2021 Nov 4.
Drought caused by various meteorological factors negatively affects vegetation. Constructing a joint probability distribution between vegetation and drought information may be appropriate to understand the vulnerability of vegetation to drought. In this study, a copula-based trivariate joint probability model is proposed to investigate the effects of various aspects of meteorological drought on vegetation (vegetation drought). Because drought can be caused by insufficient precipitation or excessive evapotranspiration, the meteorological drought risk for vegetation was divided into two aspects (atmospheric moisture supply and moisture demand). The vulnerability of vegetation drought was mapped when two aspects of meteorological drought occurred separately or simultaneously at high spatial resolution using remote sensing data. The results revealed that the response of vegetation was significantly different depending on the climatic stressors. Although the sensitivity of vegetation to each drought condition varied from region to region, it was found that vegetation was more vulnerable to drought caused by atmospheric moisture demand in most regions of Far East Asia. It has also been shown that drought conditions, which overlapped with insufficient precipitation and excessive evapotranspiration, can drive vegetation to a far more lethal level. Meanwhile, through comparison with the existing VTCI, the proposed Normalized Vegetation Temperature Condition Index (nVTCI) was found to be able to more rationally monitor vegetation drought in the Far East Asian region.
由各种气象因素引起的干旱会对植被产生负面影响。构建植被与干旱信息之间的联合概率分布可能有助于了解植被对干旱的脆弱性。在本研究中，提出了一种基于 Copula 的三变量联合概率模型，以研究各种气象干旱对植被（植被干旱）的影响。由于干旱可能是由于降水量不足或蒸散量过大引起的，因此将气象干旱风险分为两个方面（大气水分供应和水分需求）。利用遥感数据以高空间分辨率绘制了气象干旱的两个方面单独或同时发生时植被干旱的脆弱性图。结果表明，植被的响应因气候胁迫因素而异。尽管植被对每种干旱条件的敏感性在不同地区有所不同，但发现在远东地区的大多数地区，大气水分需求引起的干旱对植被的影响更为严重。此外，研究还表明，降水不足和蒸散量过大重叠的干旱条件会使植被处于更为致命的状态。同时，通过与现有 VTCI 的比较，发现所提出的归一化植被温度条件指数（nVTCI）能够更合理地监测远东地区的植被干旱。
